Mobile robot navigation has found interest during the last few years in civilian and military research areas due to its main benefit of substituting human presence in dangerous tasks. Examples include bomb deactivation, fire suppression and aerial surveillance. In literature, different definitions of the environment where the vehicles’ motion takes place are considered and the main challenge for mobile robots is to navigate in such environment guaranteeing collision avoidance and convergence towards a desired target. Firstly, in the thesis these classical environments are extended considering a more general scenario characterized by workspace bounds and an arbitrary number on objects within it. The main contribution is to develop control strategies able to perform several tasks using artificial potential functions methodologies. In particular, the first studied problem consists of a single spherical shaped agent navigating among both fixed and moving obstacles. The case of study is then extended to the multi-agent navigation problem, proposing both centralized and decentralized policies. In these problems, single integrator kinematic models are considered. The methodologies are then extended to the more realistic case of mobile robots described by a double integrator kinematic model. In the thesis, theoretical results will be developed using tools from Lyapunov stability and LaSalle’s invariance principle. The derivations will be then illustrated by a set of representative numerical examples.


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    Titel :

    Stabilization and Collision Avoidance of Non-point Agents in Dynamic Environments: A Potential Field Approach.


    Beteiligte:

    Erscheinungsdatum :

    2012-01-01


    Medientyp :

    Hochschulschrift


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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